.png&w=1536&q=75)
Agentic AI (Zero to Hero): Complete Master Series
Master the full lifecycle of agentic AI in six sessions. Start with Jev evals to measure. Build with developer patterns (PRD.md). Observe production behavior. Secure like Meta & OpenAI. Create agents with memory & learning loops. Ship live with Claude across all capability levels. Each session is standalone but together, they form the complete playbook for PMs shipping agents that work.
Fri Oct 16·4:00 PM UTC
AgenticAI (Zero to Hero): Evals revised with JEV for PMs/Eng
Jev has allowed us to re-imagine our AI agent for work and play. Most of the things that agents do requires them to make a decision before any work can be done and Jev has made making decisions cheaper, faster and deterministic (kinda deterministic with confidence). The main call is not that Jev is better than Claude, ChatGPT or Gemini. It is whether you need them for every instance or can use Jev instead and save money and time.
You'll learn from
.png)
Mahesh Yadav
AI Product Leader - Google l Meta l Microsoft l AWS | 10k+ Alums
Fri Oct 23·4:00 PM UTC
Learn to build PRDs(product req. docs) for Humans/AI agents
Most PMs still write PRDs for humans. But when Claude Code agents build from your spec, vague language breaks. Agents need explicit rules, tool definitions & guardrails, & nothing that pulls them off course. Without that, they drift & you end up re-steering every step. That’s building on vibes, and it doesn’t scale. PM 2.0 closes the gap: specs that people and agents can both follow, so your output grows without a human reviewing every decision.
You'll learn from
Mahesh Yadav
AI Product Leader - Google l Meta l Microsoft l AWS | 10k+ Alums
Fri Oct 30·4:00 PM UTC
Workshop: Build Agent Observability (Eval ++) as a FAANG PM
Most teams ship agents and hope they work. Silent failures, hallucinations, tool drift, security breaches, cost thousands before anyone notices. Observability isn’t optional; it’s your guardrail. PMs own this: you’re the link between what agents do and what users need. Understanding observability means you can delegate confidently, not nervously. You’ll know when to trust agents, when to retrain, when to escalate.
You'll learn from
Mahesh Yadav
AI Product Leader - Google l Meta l Microsoft l AWS | 10k+ Alums
Fri Nov 6·5:00 PM UTC
Secure AI Agents Against Prompt Injection as a PM
Most teams treat agent security as an afterthought, add logging later, add guardrails after the breach. That’s backwards. Meta’s Muse and OpenAI’s Dots show what happens when you bake security into the architecture from day one. Prompt injection, tool abuse, data theft. These aren’t theoretical. They cost money and reputation. PMs own this gap: you set the threat model, the constraints, the escalation rules before engineering builds.
You'll learn from
Mahesh Yadav
AI Product Leader - Google l Meta l Microsoft l AWS | 10k+ Alums
Fri Nov 13·5:00 PM UTC
Build an Agent That Learns From Your PM Work
Right now, your company’s knowledge lives everywhere: Slack threads, Google Docs, meeting notes, customer feedback, analytics dashboards, scattered across tools no one remembers. Your team makes decisions with incomplete information. Agents make decisions with even less. The real lever is centralizing context: one second brain that holds conversations, data, decisions, feedback.
You'll learn from
Mahesh Yadav
AI Product Leader - Google l Meta l Microsoft l AWS | 10k+ Alums
Fri Nov 20·5:00 PM UTC
Workshop: Build Your First Claude Agent Live as a PM
Most PMs ship Claude as a chatbot. That’s Level 1. This workshop goes to Level 4: agents that learn from your decisions. Every time you validate or reject a recommendation, it gets smarter. Stops repeating mistakes. Personalizes to how you think. Teams at Level 1 copy-paste prompts. Teams at Level 4 ship agents that improve every PM call. In 45 minutes, you move from chat to agents that learn from you. No theory. Just code that works.
You'll learn from
Mahesh Yadav
AI Product Leader - Google l Meta l Microsoft l AWS | 10k+ Alums